Shiyu Zhao

Distributed control of angle-constrained cyclic formations using bearing-only measurements

This paper studies distributed formation control of multiple agents in the plane using bearing-only measurements. It is assumed that each agent only measures the local bearings of their neighbor agents. The target formation considered in this paper is a circular formation, where each agent has exactly two neighbors. In the target formation, the angle subtended at each agent by their two neighbors is specified. We propose a distributed control law that stabilizes angle-constrained target formations merely using local bearing measurements. The stability of the target formation is analyzed based on Lyapunov approaches. We present a unified proof to show that the proposed control law can ensure local exponential or finite-time stability. The exponential or finite-time stability can be easily switched by tuning a parameter in the control law.

Bearing Rigidity and Almost Global Bearing-Only Formation Stabilization

A fundamental problem that the bearing rigidity theory studies is to determine when a framework can be uniquely determined up to a translation and a scaling factor by its inter-neighbor bearings. While many previous works focused on the bearing rigidity of two-dimensional frameworks, a first contribution of this paper is to extend these results to arbitrary dimensions. It is shown that a framework in an arbitrary dimension can be uniquely determined up to a translation and a scaling factor by the bearings if and only if the framework is infinitesimally bearing rigid. In this paper, the proposed bearing rigidity theory is further applied to the bearing-only formation stabilization problem where the target formation is defined by inter-neighbor bearings and the feedback control uses only bearing measurements. Nonlinear distributed bearing-only formation control laws are proposed for the cases with and without a global orientation. It is proved that the control laws can almost globally stabilize infinitesimally bearing rigid formations. Numerical simulations are provided to support the analysis.

Optimal sensor placement for target localisation and tracking in 2D and 3D

This paper analytically characterises optimal sensor placements for target localisation and tracking in 2D and 3D. Three types of sensors are considered: bearing-only, range-only and received-signal-strength. The optimal placement problems of the three sensor types are formulated as an identical parameter optimisation problem and consequently analysed in a unified framework. Recently developed frame theory is applied to the optimality analysis. We prove necessary and sufficient conditions for optimal placements in 2D and 3D. A number of important analytical properties of optimal placements are further explored. In order to verify the analytical analysis, we present a gradient control law that can numerically construct generic optimal placements.

Homography-based Vision-aided Inertial Navigation of UAVs in Unknown Environments

This paper investigates the navigation of small-scale unmanned aerial vehicles (UAVs) in unknown and GPS-denied environments. We consider a UAV equipped with a low-cost inertial measurement unit (IMU) and a monocular camera. The IMU can measure the specic acceleration and angular rate of the UAV. The IMU measurements are assumed to be corrupted by white noises and unknown constant biases. Hence the position, velocity and attitude of the UAV estimated by pure IMU dead reckoning will all drift over time. The monocular camera takes image sequences of the ground scene during ight. By assuming the ground scene is a level plane, the vision measurement, homography matrices, can be obtained from pairs of consecutive images. We propose a novel approach to fuse IMU and vision measurements by using an extended Kalman lter (EKF). Unlike conventional approaches, homography matrices are not required to be decomposed. Instead, they are converted to vectors and fed into the EKF directly. In the end, we analyze the observability of the proposed navigation system. We show that the velocity and attitude of the UAV and the unknown biases in IMU measurements are all observable when noisy yaw angle can be measured using a magnetometer. Numerical simulations verify our observability analysis and show that all UAV states except the position can be estimated without drift. The position drift is signicantly reduced compared to the IMU dead reckoning.

Development of an Unmanned Coaxial Rotorcraft for the DARPA UAVForge Challenge

In this paper, we present a comprehensive design for a fully functional unmanned rotorcraft system: GremLion. GremLion is a new smallscale unmanned aerial vehicle (UAV) concept using two contra-rotating rotors and one cyclic swash-plate. It can fit within a rucksack and be easily carried by a single person. GremLion is developed with all necessary avionics and a ground control station. It has been employed to participate in the 2012 UAVForge competition. The proposed design of GremLion consists of hardware construction, software development, dynamics modeling and flight control design, as well as mission algorithm investigation. A novel computer-aided technique is presented to optimize the hardware construction of GremLion to realize robust and efficient flight behavior. Based on the above hardware platform, a real-time flight control software and a ground control station (GCS) software have been developed to achieve the onboard processing capability and the ground monitoring capability respectively. A GremLion mathematical model has been derived for hover and near hover flight conditions and identified from experimental data collected in flight tests. We have combined H1 technique, a robust and perfect tracking (RPT) approach, and custom-defined flight scheduling to design a comprehensive nonlinear flight control law for GremLion and successfully realized the automatic control which includes take-off, hovering, and a variety of essential flight motions. In addition, advanced mission algorithms have been presented in the paper, including obstacle detection and avoidance, as well as target following. Both ground and flight experiments of the complete system have been conducted including autonomous hovering, waypoint flight, etc. The test results have been presented in this paper to verify the proposed design methodology.

A Robust Real-Time Vision System for Autonomous Cargo Transfer by an Unmanned Helicopter

Motivated by the 2013 International UAV Innovation Grand Prix, we design and implement a real-time vision system for an unmanned helicopter autonomously transferring cargoes between two platforms. In the competition, four cargoes are initially placed inside four circles on one platform, respectively. They are required to be transferred one by one into the four circles on the other platform. This paper presents the core algorithms of the proposed vision system on ellipse detection, ellipse tracking, and single-circle-based position estimation. Experiments and the great success of our team in the competition have verified the efficiency, accuracy, and robustness of the algorithms. Our team was ranked first in the final round competition.

Translational and Scaling Formation Maneuver Control via a Bearing-Based Approach

This paper studies distributed maneuver control of multiagent formations in arbitrary dimensions. The objective is to control the translation and scale of the formation while maintaining the desired formation pattern. Unlike conventional approaches where the target formation is defined by relative positions or distances, we propose a novel bearing-based approach where the target formation is defined by inter-neighbor bearings. Since the bearings are invariant to the translation and scale of the formation, the bearing-based approach provides a simple solution to the problem of translational and scaling formation maneuver control. Linear formation control laws for double-integrator dynamics are proposed and the global formation stability is analyzed. This paper also studies bearing-based formation control in the presence of practical problems, including input disturbances, acceleration saturation, and collision avoidance. The theoretical results are illustrated with numerical simulations.

Localizability and distributed protocols for bearing-based network localization in arbitrary dimensions

This paper addresses the problem of bearing-based network localization, which aims to localize all the nodes in a static network given the locations of a subset of nodes termed anchors and inter-node bearings measured in a common reference frame. The contributions of the paper are twofold. Firstly, we propose necessary and sufficient conditions for network localizability with both algebraic and rigidity theoretic interpretations. The analysis of the localizability heavily relies on the recently developed bearing rigidity theory and a special matrix termed the bearing Laplacian. Secondly, we propose a linear distributed protocol for bearing-based network localization. The protocol can globally localize a network if and only if the network is localizable. The sensitivity of the protocol to constant measurement errors is also analyzed. One novelty of this work is that the localizability analysis and localization protocol are applicable to networks in arbitrary dimensional spaces.

Finite-time stabilisation of cyclic formations using bearing-only measurements

This paper studies decentralised formation control of multiple vehicles in the plane when each vehicle can only measure the local bearings of their neighbours by using bearing-only sensors. Since the inter-vehicle distance cannot be measured, the target formation involves no distance constraints. More specifically, the target formation considered in this paper is an angle-constrained cyclic formation, where each vehicle has exactly two neighbours and the angle at each vehicle subtended by its two neighbours is pre-specified. To stabilise the target formation, we propose a discontinuous control law that only requires the sign information of the angle errors. Due to the discontinuity of the proposed control law, the stability of the closed-loop system is analysed by employing a locally Lipschitz Lyapunov function and nonsmooth analysis tools. We prove that the target formation is locally finite-time stable with collision avoidance guaranteed.

Vision-aided Estimation of Attitude, Velocity, and Inertial Measurement Bias for UAV Stabilization

This paper studies vision-aided inertial navigation of small-scale unmanned aerial vehicles (UAVs) in GPS-denied environments. The objectives of the navigation system are to firstly online estimate and compensate the unknown inertial measurement biases, secondly provide drift-free velocity and attitude estimates which are crucial for UAV stabilization control, and thirdly give relatively accurate position estimation such that the UAV is able to perform at least a short-term navigation when the GPS signal is not available. For the vision system, we do not presume maps or landmarks of the environment. The vision system should be able to work robustly even given low-resolution images (e.g., 160 ×120 pixels) of near homogeneous visual features. To achieve these objectives, we propose a novel homography-based vision-aided navigation system that adopts four common sensors: a low-cost inertial measurement unit, a downward-looking monocular camera, a barometer, and a compass. The measurements of the sensors are fused by an extended Kalman filter. Based on both analytical and numerical observability analyses of the navigation system, we theoretically verify that the proposed navigation system is able to achieve the navigation objectives. We also show comprehensive simulation and real flight experimental results to verify the effectiveness and robustness of the proposed navigation system.